Losing a limb is life changing…and expensive
The loss of a limb can be devastating to a person’s life. As well as the impact to mobility, independence and participation in day-to-day activities, it can also have a significant impact on a person’s relationships, community and social life. To add to this, an amputation can radically change how a person views themselves and their future. Amputees often have to cope with ongoing health issues (e.g., pain), learn new skills, and adjust their expectations about their capabilities.
Not only is an amputation a major life changing event for a person; the burden and cost of ulceration on the UK NHS is over £5bn pounds a year. One in four people with diabetes will develop a foot ulcer in their lifetime. Of those, about a quarter will require a lower limb amputation as a life-saving procedure.
Astoundingly, though, experts believe that with more proactive care up to half of all amputations could be avoided. A significant challenge for at-risk individuals is accessing effective care early and having the information and tools to self-care thereafter. To avoid eventual amputation, leg and foot ulcers and associated problems need to be treated quickly and correctly to reduce the risk of non-healing wounds, secondary health problems and deteriorating health1.
Researchers at Manchester Met have made a breakthrough
Imagine what would change if AI could offer early detection of ulcers, and proactively refer patients for care. For example, if AI could assist a patient, their carer, or a relatively low-skilled clinician, to identify early and monitor the progression of a foot or leg ulcer? Not only could the patient avoid an amputation; such a solution would also deliver significant time and cost-savings for health services. A clinical tool that is simple to use, widely accessible, and scientifically robust could relieve clinical burden and provide a paradigm-shift for diabetic footcare.
A team of researchers at Manchester Metropolitan University, co-led by Prof. Neil Reeves and Dr. Moi Hoon Yap, have been working on a solution to achieve just that. Enabled by Oracle’s high performance computing, they have developed AI algorithms that use computer vision technology to identify a foot ulcer at various stages of its development. Based on robust lab testing, the application, called FootSnap AI, can automatically identify diabetic foot ulcers and associated pathologies using deep learning.
Developed using thousands of diabetic foot images and subjected to extensive scientific peer review and published in a number of medical and computer vision journals234, in lab trials, FootSnap AI has a high sensitivity (0.934) and specificity (0.911) in identifying diabetic foot ulcers from foot images.
Testing in a real world setting
The NHS Manchester Amputation Reduction Strategy (The MARS Project) , which Oracle has also been supporting, will be shortly commencing a programme to test the efficacy of the technology in a real world setting.
The original performance of the standalone mobile app was constrained by its hardware capability and could only support a light-weight AI/deep learning model. Built on AI technology developed by Manchester Met and now using Oracle cloud infrastructure, FootSnap AI is scalable and can respond to new demands rapidly. The cloud infrastructure equipped with GPU can speed up the inference time and provide better accuracy in ulcer detection.
“Understanding the treatment of ulceration and whether these wounds are getting better or worse is essentially pattern recognition. Further, the real breakthrough will come if we - health professionals and patients - can identify these wounds much earlier and therefore initiate much more timely treatment. This is where artificial intelligence is potentially a game changer,” says Naseer Ahmad, Consultant Vascular Surgeon at Manchester University NHS Foundation Trust.
“Oracle Cloud has provided the framework for our AI architecture to be deployed to the cloud as a service to mobile clients. Oracle Cloud delivers an online enterprise scale solution where our data can be stored, processed, and monitored seamlessly using state of the art web technologies.,” says Bill Cassidy, Research Associate at Manchester Metropolitan University, in Manchester, UK.
1An NHS England study estimates that having effective care early, reduces leg ulcer healing times from approximately two years to just a few months and is 10 times less expensive. But many patients suffer unnecessarily for several years due to a lack of knowledge and not accessing the right care. NHS England (2017). NHS RightCare scenario: The variation between sub-optimal and optimal pathways.
2 Goyal, M., Reeves, N., Rajbhandari, S., & Yap, M. H. (2019). Robust Methods for Real-Time Diabetic Foot Ulcer Detection and Localization on Mobile Devices. IEEE Journal of Biomedical and Health Informatics. 23(4), 1730-1741, doi:10.1109/JBHI.2018.2868656
3Yap, M. H., Chatwin, K. E., Ng, C. C., Abbott, C. A., Bowling, F. L., Rajbhandari, S., . . . Reeves, N. D. (2018). A New Mobile Application for Standardizing Diabetic Foot Images. Journal of Diabetes Science and Technology, 12(1), 169-173. doi:10.1177/1932296817713761
4Goyal, M., Reeves, N. D., Davison, A. K., Rajbhandari, S., Spragg, J., & Yap, M. H. (2018). DFUNet: Convolutional Neural Networks for Diabetic Foot Ulcer Classification. IEEE Transactions on Emerging Topics in Computational Intelligence. doi: 10.1109/TETCI.2018.2866254